Análise Exploratória - Mercado Imobiliário de Melbourne

Dataset statistics

Number of variables	21
Number of observations	13580
Missing cells	13256
Missing cells (%)	4.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.2 MiB
Average record size in memory	168.0 B

Variable types

Categorical	8
Numeric	13

Warnings

`Suburb` has a high cardinality: 314 distinct values	High cardinality
`Address` has a high cardinality: 13378 distinct values	High cardinality
`SellerG` has a high cardinality: 268 distinct values	High cardinality
`Date` has a high cardinality: 58 distinct values	High cardinality
`Rooms` is highly correlated with `Bedroom2`	High correlation
`Bedroom2` is highly correlated with `Rooms`	High correlation
`BuildingArea` has 6450 (47.5%) missing values	Missing
`YearBuilt` has 5375 (39.6%) missing values	Missing
`CouncilArea` has 1369 (10.1%) missing values	Missing
`Landsize` is highly skewed (γ1 = 95.23740045)	Skewed
`BuildingArea` is highly skewed (γ1 = 77.69154092)	Skewed
`Address` is uniformly distributed	Uniform
`Car` has 1026 (7.6%) zeros	Zeros
`Landsize` has 1939 (14.3%) zeros	Zeros

Reproduction

Analysis started	2021-03-29 17:02:08.243854
Analysis finished	2021-03-29 17:02:40.812171
Duration	32.57 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

Suburb
Categorical

HIGH CARDINALITY

Distinct	314
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Memory size	106.2 KiB

Reservoir	359
Richmond	260
Bentleigh East	249
Preston	239
Brunswick	222
Other values (309)	12251

Length

Max length	18
Median length	9
Mean length	9.79646539
Min length	3

Characters and Unicode

Total characters	133036
Distinct characters	49
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	21 ?
Unique (%)	0.2%

Sample

1st row	Abbotsford
2nd row	Abbotsford
3rd row	Abbotsford
4th row	Abbotsford
5th row	Abbotsford

Value	Count	Frequency (%)
Reservoir	359	2.6%
Richmond	260	1.9%
Bentleigh East	249	1.8%
Preston	239	1.8%
Brunswick	222	1.6%
Essendon	220	1.6%
South Yarra	202	1.5%
Glen Iris	195	1.4%
Hawthorn	191	1.4%
Coburg	190	1.4%
Other values (304)	11253	82.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
east	1042	5.6%
north	735	3.9%
south	531	2.8%
west	509	2.7%
brunswick	420	2.3%
melbourne	418	2.2%
bentleigh	388	2.1%
reservoir	359	1.9%
brighton	324	1.7%
hawthorn	310	1.7%
Other values (265)	13616	73.0%

Most occurring characters

Value	Count	Frequency (%)
e	12017	9.0%
o	11338	8.5%
r	11177	8.4%
n	9667	7.3%
a	8724	6.6%
t	8260	6.2%
l	7303	5.5%
i	6507	4.9%
s	6373	4.8%
	5072	3.8%
Other values (39)	46598	35.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	109304	82.2%
Uppercase Letter	18660	14.0%
Space Separator	5072	3.8%

Most frequent character per category

Value	Count	Frequency (%)
e	12017	11.0%
o	11338	10.4%
r	11177	10.2%
n	9667	8.8%
a	8724	8.0%
t	8260	7.6%
l	7303	6.7%
i	6507	6.0%
s	6373	5.8%
h	4409	4.0%
Other values (15)	23529	21.5%

Value	Count	Frequency (%)
B	1957	10.5%
E	1632	8.7%
M	1491	8.0%
S	1439	7.7%
H	1408	7.5%
C	1249	6.7%
P	1221	6.5%
N	1185	6.4%
W	1017	5.5%
A	932	5.0%
Other values (13)	5129	27.5%

Value	Count	Frequency (%)
	5072	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	127964	96.2%
Common	5072	3.8%

Most frequent character per script

Value	Count	Frequency (%)
e	12017	9.4%
o	11338	8.9%
r	11177	8.7%
n	9667	7.6%
a	8724	6.8%
t	8260	6.5%
l	7303	5.7%
i	6507	5.1%
s	6373	5.0%
h	4409	3.4%
Other values (38)	42189	33.0%

Value	Count	Frequency (%)
	5072	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	133036	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	12017	9.0%
o	11338	8.5%
r	11177	8.4%
n	9667	7.3%
a	8724	6.6%
t	8260	6.2%
l	7303	5.5%
i	6507	4.9%
s	6373	4.8%
	5072	3.8%
Other values (39)	46598	35.0%

Address
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	13378
Distinct (%)	98.5%
Missing	0
Missing (%)	0.0%
Memory size	106.2 KiB

5 Margaret St	3
2 Bruce St	3
53 William St	3
14 Arthur St	3
36 Aberfeldie St	3
Other values (13373)	13565

Length

Max length	27
Median length	13
Mean length	13.51045655
Min length	8

Characters and Unicode

Total characters	183472
Distinct characters	64
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	13185 ?
Unique (%)	97.1%

Sample

1st row	85 Turner St
2nd row	25 Bloomburg St
3rd row	5 Charles St
4th row	40 Federation La
5th row	55a Park St

Value	Count	Frequency (%)
5 Margaret St	3	< 0.1%
2 Bruce St	3	< 0.1%
53 William St	3	< 0.1%
14 Arthur St	3	< 0.1%
36 Aberfeldie St	3	< 0.1%
5 Charles St	3	< 0.1%
28 Blair St	3	< 0.1%
13 Robinson St	3	< 0.1%
1/1 Clarendon St	3	< 0.1%
11 Duffy St	2	< 0.1%
Other values (13368)	13551	99.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
st	8052	19.7%
rd	2825	6.9%
ct	612	1.5%
dr	447	1.1%
av	321	0.8%
gr	311	0.8%
3	260	0.6%
4	257	0.6%
5	251	0.6%
7	241	0.6%
Other values (7068)	27329	66.8%

Most occurring characters

Value	Count	Frequency (%)
	27326	14.9%
t	12785	7.0%
e	9573	5.2%
S	9002	4.9%
r	8628	4.7%
a	8075	4.4%
n	7309	4.0%
1	7036	3.8%
o	6788	3.7%
l	6303	3.4%
Other values (54)	80647	44.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	92167	50.2%
Decimal Number	32266	17.6%
Uppercase Letter	27779	15.1%
Space Separator	27326	14.9%
Other Punctuation	3934	2.1%

Most frequent character per category

Value	Count	Frequency (%)
S	9002	32.4%
R	3536	12.7%
C	2148	7.7%
B	1419	5.1%
M	1303	4.7%
A	1299	4.7%
D	1122	4.0%
P	1102	4.0%
G	1093	3.9%
H	926	3.3%
Other values (16)	4829	17.4%

Value	Count	Frequency (%)
t	12785	13.9%
e	9573	10.4%
r	8628	9.4%
a	8075	8.8%
n	7309	7.9%
o	6788	7.4%
l	6303	6.8%
d	5940	6.4%
i	5031	5.5%
s	3384	3.7%
Other values (16)	18351	19.9%

Value	Count	Frequency (%)
1	7036	21.8%
2	4894	15.2%
3	3833	11.9%
4	3129	9.7%
5	2756	8.5%
6	2445	7.6%
7	2218	6.9%
0	2146	6.7%
8	2020	6.3%
9	1789	5.5%

Value	Count	Frequency (%)
	27326	100.0%

Value	Count	Frequency (%)
/	3934	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	119946	65.4%
Common	63526	34.6%

Most frequent character per script

Value	Count	Frequency (%)
t	12785	10.7%
e	9573	8.0%
S	9002	7.5%
r	8628	7.2%
a	8075	6.7%
n	7309	6.1%
o	6788	5.7%
l	6303	5.3%
d	5940	5.0%
i	5031	4.2%
Other values (42)	40512	33.8%

Value	Count	Frequency (%)
	27326	43.0%
1	7036	11.1%
2	4894	7.7%
/	3934	6.2%
3	3833	6.0%
4	3129	4.9%
5	2756	4.3%
6	2445	3.8%
7	2218	3.5%
0	2146	3.4%
Other values (2)	3809	6.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	183472	100.0%

Most frequent character per block

Value	Count	Frequency (%)
	27326	14.9%
t	12785	7.0%
e	9573	5.2%
S	9002	4.9%
r	8628	4.7%
a	8075	4.4%
n	7309	4.0%
1	7036	3.8%
o	6788	3.7%
l	6303	3.4%
Other values (54)	80647	44.0%

Rooms
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	9
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2.937997054
Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	106.2 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	3
95-th percentile	5
Maximum	10
Range	9
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9557479384
Coefficient of variation (CV)	0.3253059553
Kurtosis	0.7940679895
Mean	2.937997054
Median Absolute Deviation (MAD)	1
Skewness	0.3764780328
Sum	39898
Variance	0.9134541218
Monotocity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
3	5881	43.3%
2	3648	26.9%
4	2688	19.8%
1	681	5.0%
5	596	4.4%
6	67	0.5%
7	10	0.1%
8	8	0.1%
10	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	681	5.0%
2	3648	26.9%
3	5881	43.3%
4	2688	19.8%
5	596	4.4%

Value	Count	Frequency (%)
10	1	< 0.1%
8	8	0.1%
7	10	0.1%
6	67	0.5%
5	596	4.4%

Type
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	106.2 KiB

h	9449
u	3017
t	1114

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	13580
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	h
2nd row	h
3rd row	h
4th row	h
5th row	h

Value	Count	Frequency (%)
h	9449	69.6%
u	3017	22.2%
t	1114	8.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
h	9449	69.6%
u	3017	22.2%
t	1114	8.2%

Most occurring characters

Value	Count	Frequency (%)
h	9449	69.6%
u	3017	22.2%
t	1114	8.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	13580	100.0%

Most frequent character per category

Value	Count	Frequency (%)
h	9449	69.6%
u	3017	22.2%
t	1114	8.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	13580	100.0%

Most frequent character per script

Value	Count	Frequency (%)
h	9449	69.6%
u	3017	22.2%
t	1114	8.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13580	100.0%

Most frequent character per block

Value	Count	Frequency (%)
h	9449	69.6%
u	3017	22.2%
t	1114	8.2%

Price
Real number (ℝ_≥0)

Distinct	2204
Distinct (%)	16.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1075684.079
Minimum	85000
Maximum	9000000
Zeros	0
Zeros (%)	0.0%
Memory size	106.2 KiB

Quantile statistics

Minimum	85000
5-th percentile	405000
Q1	650000
median	903000
Q3	1330000
95-th percentile	2290050
Maximum	9000000
Range	8915000
Interquartile range (IQR)	680000

Descriptive statistics

Standard deviation	639310.7243
Coefficient of variation (CV)	0.5943294472
Kurtosis	9.874338886
Mean	1075684.079
Median Absolute Deviation (MAD)	313000
Skewness	2.239624313
Sum	1.46077898 × 10¹⁰
Variance	4.087182022 × 10¹¹
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1100000	113	0.8%
1300000	109	0.8%
800000	109	0.8%
650000	109	0.8%
600000	104	0.8%
1000000	97	0.7%
1200000	97	0.7%
900000	95	0.7%
700000	91	0.7%
1400000	89	0.7%
Other values (2194)	12567	92.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
85000	1	< 0.1%
131000	1	< 0.1%
145000	2	< 0.1%
160000	1	< 0.1%
170000	2	< 0.1%

Value	Count	Frequency (%)
9000000	1	< 0.1%
8000000	1	< 0.1%
7650000	1	< 0.1%
6500000	1	< 0.1%
6400000	1	< 0.1%

Method
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	106.2 KiB

S	9022
SP	1703
PI	1564
VB	1199
SA	92

Length

Max length	2
Median length	1
Mean length	1.335640648
Min length	1

Characters and Unicode

Total characters	18138
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	S
2nd row	S
3rd row	SP
4th row	PI
5th row	VB

Value	Count	Frequency (%)
S	9022	66.4%
SP	1703	12.5%
PI	1564	11.5%
VB	1199	8.8%
SA	92	0.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
s	9022	66.4%
sp	1703	12.5%
pi	1564	11.5%
vb	1199	8.8%
sa	92	0.7%

Most occurring characters

Value	Count	Frequency (%)
S	10817	59.6%
P	3267	18.0%
I	1564	8.6%
V	1199	6.6%
B	1199	6.6%
A	92	0.5%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	18138	100.0%

Most frequent character per category

Value	Count	Frequency (%)
S	10817	59.6%
P	3267	18.0%
I	1564	8.6%
V	1199	6.6%
B	1199	6.6%
A	92	0.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	18138	100.0%

Most frequent character per script

Value	Count	Frequency (%)
S	10817	59.6%
P	3267	18.0%
I	1564	8.6%
V	1199	6.6%
B	1199	6.6%
A	92	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	18138	100.0%

Most frequent character per block

Value	Count	Frequency (%)
S	10817	59.6%
P	3267	18.0%
I	1564	8.6%
V	1199	6.6%
B	1199	6.6%
A	92	0.5%

SellerG
Categorical

HIGH CARDINALITY

Distinct	268
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	106.2 KiB

Nelson	1565
Jellis	1316
hockingstuart	1167
Barry	1011
Ray	701
Other values (263)	7820

Length

Max length	23
Median length	6
Mean length	6.402503682
Min length	1

Characters and Unicode

Total characters	86946
Distinct characters	57
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	78 ?
Unique (%)	0.6%

Sample

1st row	Biggin
2nd row	Biggin
3rd row	Biggin
4th row	Biggin
5th row	Nelson

Value	Count	Frequency (%)
Nelson	1565	11.5%
Jellis	1316	9.7%
hockingstuart	1167	8.6%
Barry	1011	7.4%
Ray	701	5.2%
Marshall	659	4.9%
Buxton	632	4.7%
Biggin	393	2.9%
Brad	342	2.5%
Fletchers	301	2.2%
Other values (258)	5493	40.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
nelson	1565	11.5%
jellis	1316	9.7%
hockingstuart	1167	8.6%
barry	1011	7.4%
ray	701	5.2%
marshall	659	4.9%
buxton	632	4.7%
biggin	393	2.9%
brad	342	2.5%
woodards	301	2.2%
Other values (255)	5493	40.4%

Most occurring characters

Value	Count	Frequency (%)
l	7767	8.9%
a	7196	8.3%
s	6910	7.9%
r	6662	7.7%
e	6538	7.5%
o	5706	6.6%
n	5268	6.1%
i	4936	5.7%
t	4061	4.7%
h	2851	3.3%
Other values (47)	29051	33.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	72731	83.7%
Uppercase Letter	13923	16.0%
Other Punctuation	178	0.2%
Decimal Number	114	0.1%

Most frequent character per category

Value	Count	Frequency (%)
B	2654	19.1%
N	1852	13.3%
J	1617	11.6%
R	1303	9.4%
M	1294	9.3%
G	674	4.8%
W	584	4.2%
H	478	3.4%
S	413	3.0%
C	403	2.9%
Other values (15)	2651	19.0%

Value	Count	Frequency (%)
l	7767	10.7%
a	7196	9.9%
s	6910	9.5%
r	6662	9.2%
e	6538	9.0%
o	5706	7.8%
n	5268	7.2%
i	4936	6.8%
t	4061	5.6%
h	2851	3.9%
Other values (15)	14836	20.4%

Value	Count	Frequency (%)
'	106	59.6%
&	32	18.0%
.	29	16.3%
/	9	5.1%
@	2	1.1%

Value	Count	Frequency (%)
2	57	50.0%
1	57	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	86654	99.7%
Common	292	0.3%

Most frequent character per script

Value	Count	Frequency (%)
l	7767	9.0%
a	7196	8.3%
s	6910	8.0%
r	6662	7.7%
e	6538	7.5%
o	5706	6.6%
n	5268	6.1%
i	4936	5.7%
t	4061	4.7%
h	2851	3.3%
Other values (40)	28759	33.2%

Value	Count	Frequency (%)
'	106	36.3%
2	57	19.5%
1	57	19.5%
&	32	11.0%
.	29	9.9%
/	9	3.1%
@	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	86946	100.0%

Most frequent character per block

Value	Count	Frequency (%)
l	7767	8.9%
a	7196	8.3%
s	6910	7.9%
r	6662	7.7%
e	6538	7.5%
o	5706	6.6%
n	5268	6.1%
i	4936	5.7%
t	4061	4.7%
h	2851	3.3%
Other values (47)	29051	33.4%

Date
Categorical

HIGH CARDINALITY

Distinct	58
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	106.2 KiB

27/05/2017	473
3/06/2017	395
12/08/2017	387
17/06/2017	374
27/11/2016	362
Other values (53)	11589

Length

Max length	10
Median length	10
Mean length	9.724815906
Min length	9

Characters and Unicode

Total characters	132063
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3/12/2016
2nd row	4/02/2016
3rd row	4/03/2017
4th row	4/03/2017
5th row	4/06/2016

Value	Count	Frequency (%)
27/05/2017	473	3.5%
3/06/2017	395	2.9%
12/08/2017	387	2.8%
17/06/2017	374	2.8%
27/11/2016	362	2.7%
29/07/2017	341	2.5%
4/03/2017	337	2.5%
25/02/2017	333	2.5%
24/06/2017	329	2.4%
10/12/2016	319	2.3%
Other values (48)	9930	73.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
27/05/2017	473	3.5%
3/06/2017	395	2.9%
12/08/2017	387	2.8%
17/06/2017	374	2.8%
27/11/2016	362	2.7%
29/07/2017	341	2.5%
4/03/2017	337	2.5%
25/02/2017	333	2.5%
24/06/2017	329	2.4%
10/12/2016	319	2.3%
Other values (48)	9930	73.1%

Most occurring characters

Value	Count	Frequency (%)
/	27160	20.6%
0	26427	20.0%
1	22198	16.8%
2	21040	15.9%
7	11327	8.6%
6	9451	7.2%
8	3453	2.6%
9	3075	2.3%
5	2954	2.2%
3	2690	2.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	104903	79.4%
Other Punctuation	27160	20.6%

Most frequent character per category

Value	Count	Frequency (%)
0	26427	25.2%
1	22198	21.2%
2	21040	20.1%
7	11327	10.8%
6	9451	9.0%
8	3453	3.3%
9	3075	2.9%
5	2954	2.8%
3	2690	2.6%
4	2288	2.2%

Value	Count	Frequency (%)
/	27160	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	132063	100.0%

Most frequent character per script

Value	Count	Frequency (%)
/	27160	20.6%
0	26427	20.0%
1	22198	16.8%
2	21040	15.9%
7	11327	8.6%
6	9451	7.2%
8	3453	2.6%
9	3075	2.3%
5	2954	2.2%
3	2690	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	132063	100.0%

Most frequent character per block

Value	Count	Frequency (%)
/	27160	20.6%
0	26427	20.0%
1	22198	16.8%
2	21040	15.9%
7	11327	8.6%
6	9451	7.2%
8	3453	2.6%
9	3075	2.3%
5	2954	2.2%
3	2690	2.0%

Distance
Real number (ℝ_≥0)

Distinct	202
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	10.13777614
Minimum	0
Maximum	48.1
Zeros	6
Zeros (%)	< 0.1%
Memory size	106.2 KiB

Quantile statistics

Minimum	0
5-th percentile	2.6
Q1	6.1
median	9.2
Q3	13
95-th percentile	20.6
Maximum	48.1
Range	48.1
Interquartile range (IQR)	6.9

Descriptive statistics

Standard deviation	5.868724943
Coefficient of variation (CV)	0.5788966792
Kurtosis	5.260001109
Mean	10.13777614
Median Absolute Deviation (MAD)	3.35
Skewness	1.676937083
Sum	137671
Variance	34.44193246
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11.2	739	5.4%
9.2	367	2.7%
13.9	324	2.4%
7.8	306	2.3%
4.6	263	1.9%
13	252	1.9%
8	248	1.8%
5.2	248	1.8%
13.8	237	1.7%
2.6	235	1.7%
Other values (192)	10361	76.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	6	< 0.1%
0.7	8	0.1%
1.2	33	0.2%
1.3	5	< 0.1%
1.5	17	0.1%

Value	Count	Frequency (%)
48.1	1	< 0.1%
47.4	1	< 0.1%
47.3	3	< 0.1%
45.9	9	0.1%
45.2	1	< 0.1%

Postcode
Real number (ℝ_≥0)

Distinct	198
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3105.301915
Minimum	3000
Maximum	3977
Zeros	0
Zeros (%)	0.0%
Memory size	106.2 KiB

Quantile statistics

Minimum	3000
5-th percentile	3013
Q1	3044
median	3084
Q3	3148
95-th percentile	3204
Maximum	3977
Range	977
Interquartile range (IQR)	104

Descriptive statistics

Standard deviation	90.67696409
Coefficient of variation (CV)	0.02920069178
Kurtosis	29.15686787
Mean	3105.301915
Median Absolute Deviation (MAD)	50
Skewness	4.076152215
Sum	42170000
Variance	8222.311816
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3073	359	2.6%
3020	306	2.3%
3121	292	2.2%
3040	290	2.1%
3046	284	2.1%
3165	249	1.8%
3058	246	1.8%
3163	245	1.8%
3012	242	1.8%
3072	239	1.8%
Other values (188)	10828	79.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3000	46	0.3%
3002	22	0.2%
3003	31	0.2%
3006	41	0.3%
3008	3	< 0.1%

Value	Count	Frequency (%)
3977	8	0.1%
3976	4	< 0.1%
3910	6	< 0.1%
3810	3	< 0.1%
3809	1	< 0.1%

Bedroom2
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	12
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2.914727541
Minimum	0
Maximum	20
Zeros	16
Zeros (%)	0.1%
Memory size	106.2 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	3
Q3	3
95-th percentile	4
Maximum	20
Range	20
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9659210617
Coefficient of variation (CV)	0.33139326
Kurtosis	8.074963808
Mean	2.914727541
Median Absolute Deviation (MAD)	1
Skewness	0.7740822106
Sum	39582
Variance	0.9330034975
Monotocity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
3	5896	43.4%
2	3737	27.5%
4	2601	19.2%
1	691	5.1%
5	556	4.1%
6	63	0.5%
0	16	0.1%
7	10	0.1%
8	5	< 0.1%
9	3	< 0.1%
Other values (2)	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	16	0.1%
1	691	5.1%
2	3737	27.5%
3	5896	43.4%
4	2601	19.2%

Value	Count	Frequency (%)
20	1	< 0.1%
10	1	< 0.1%
9	3	< 0.1%
8	5	< 0.1%
7	10	0.1%

Bathroom
Real number (ℝ_≥0)

Distinct	9
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.534241532
Minimum	0
Maximum	8
Zeros	34
Zeros (%)	0.3%
Memory size	106.2 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	3
Maximum	8
Range	8
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.6917117225
Coefficient of variation (CV)	0.4508493012
Kurtosis	3.594973134
Mean	1.534241532
Median Absolute Deviation (MAD)	0
Skewness	1.377405972
Sum	20835
Variance	0.478465107
Monotocity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
1	7512	55.3%
2	4974	36.6%
3	917	6.8%
4	106	0.8%
0	34	0.3%
5	28	0.2%
6	5	< 0.1%
8	2	< 0.1%
7	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	34	0.3%
1	7512	55.3%
2	4974	36.6%
3	917	6.8%
4	106	0.8%

Value	Count	Frequency (%)
8	2	< 0.1%
7	2	< 0.1%
6	5	< 0.1%
5	28	0.2%
4	106	0.8%

Car
Real number (ℝ_≥0)

ZEROS

Distinct	11
Distinct (%)	0.1%
Missing	62
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%

Mean	1.610075455
Minimum	0
Maximum	10
Zeros	1026
Zeros (%)	7.6%
Memory size	106.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	2
Q3	2
95-th percentile	3
Maximum	10
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9626335192
Coefficient of variation (CV)	0.5978809976
Kurtosis	5.193182788
Mean	1.610075455
Median Absolute Deviation (MAD)	1
Skewness	1.369675926
Sum	21765
Variance	0.9266632924
Monotocity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
2	5591	41.2%
1	5509	40.6%
0	1026	7.6%
3	748	5.5%
4	506	3.7%
5	63	0.5%
6	54	0.4%
8	9	0.1%
7	8	0.1%
10	3	< 0.1%
(Missing)	62	0.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1026	7.6%
1	5509	40.6%
2	5591	41.2%
3	748	5.5%
4	506	3.7%

Value	Count	Frequency (%)
10	3	< 0.1%
9	1	< 0.1%
8	9	0.1%
7	8	0.1%
6	54	0.4%

Landsize
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	1448
Distinct (%)	10.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	558.4161267
Minimum	0
Maximum	433014
Zeros	1939
Zeros (%)	14.3%
Memory size	106.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	177
median	440
Q3	651
95-th percentile	995
Maximum	433014
Range	433014
Interquartile range (IQR)	474

Descriptive statistics

Standard deviation	3990.669241
Coefficient of variation (CV)	7.146407581
Kurtosis	10180.34683
Mean	558.4161267
Median Absolute Deviation (MAD)	236
Skewness	95.23740045
Sum	7583291
Variance	15925440.99
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1939	14.3%
650	103	0.8%
697	71	0.5%
700	48	0.4%
585	47	0.3%
534	42	0.3%
590	39	0.3%
696	36	0.3%
649	36	0.3%
604	35	0.3%
Other values (1438)	11184	82.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1939	14.3%
1	2	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
5	1	< 0.1%

Value	Count	Frequency (%)
433014	1	< 0.1%
76000	1	< 0.1%
75100	1	< 0.1%
44500	1	< 0.1%
41400	1	< 0.1%

BuildingArea
Real number (ℝ_≥0)

MISSING
SKEWED

Distinct	602
Distinct (%)	8.4%
Missing	6450
Missing (%)	47.5%
Infinite	0
Infinite (%)	0.0%

Mean	151.9676499
Minimum	0
Maximum	44515
Zeros	17
Zeros (%)	0.1%
Memory size	106.2 KiB

Quantile statistics

Minimum	0
5-th percentile	51
Q1	93
median	126
Q3	174
95-th percentile	294
Maximum	44515
Range	44515
Interquartile range (IQR)	81

Descriptive statistics

Standard deviation	541.0145376
Coefficient of variation (CV)	3.560063856
Kurtosis	6347.802222
Mean	151.9676499
Median Absolute Deviation (MAD)	39
Skewness	77.69154092
Sum	1083529.344
Variance	292696.7299
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
120	114	0.8%
110	89	0.7%
100	88	0.6%
130	84	0.6%
115	77	0.6%
150	74	0.5%
104	66	0.5%
90	65	0.5%
140	64	0.5%
85	63	0.5%
Other values (592)	6346	46.7%
(Missing)	6450	47.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	17	0.1%
1	11	0.1%
2	16	0.1%
3	20	0.1%
4	4	< 0.1%

Value	Count	Frequency (%)
44515	1	< 0.1%
6791	1	< 0.1%
3558	1	< 0.1%
3112	1	< 0.1%
1561	1	< 0.1%

YearBuilt
Real number (ℝ_≥0)

MISSING

Distinct	144
Distinct (%)	1.8%
Missing	5375
Missing (%)	39.6%
Infinite	0
Infinite (%)	0.0%

Mean	1964.684217
Minimum	1196
Maximum	2018
Zeros	0
Zeros (%)	0.0%
Memory size	106.2 KiB

Quantile statistics

Minimum	1196
5-th percentile	1900
Q1	1940
median	1970
Q3	1999
95-th percentile	2012
Maximum	2018
Range	822
Interquartile range (IQR)	59

Descriptive statistics

Standard deviation	37.27376222
Coefficient of variation (CV)	0.01897188459
Kurtosis	21.22603222
Mean	1964.684217
Median Absolute Deviation (MAD)	30
Skewness	-1.54127876
Sum	16120234
Variance	1389.33335
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1970	866	6.4%
1960	725	5.3%
1950	580	4.3%
1900	341	2.5%
1980	338	2.5%
2000	300	2.2%
1920	280	2.1%
1930	274	2.0%
1910	240	1.8%
1940	238	1.8%
Other values (134)	4023	29.6%
(Missing)	5375	39.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1196	1	< 0.1%
1830	1	< 0.1%
1850	4	< 0.1%
1854	1	< 0.1%
1856	1	< 0.1%

Value	Count	Frequency (%)
2018	1	< 0.1%
2017	18	0.1%
2016	58	0.4%
2015	65	0.5%
2014	100	0.7%

CouncilArea
Categorical

MISSING

Distinct	33
Distinct (%)	0.3%
Missing	1369
Missing (%)	10.1%
Memory size	106.2 KiB

Moreland	1163
Boroondara	1160
Moonee Valley	997
Darebin	934
Glen Eira	848
Other values (28)	7109

Length

Max length	17
Median length	9
Mean length	9.069281795
Min length	4

Characters and Unicode

Total characters	110745
Distinct characters	39
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	< 0.1%

Sample

1st row	Yarra
2nd row	Yarra
3rd row	Yarra
4th row	Yarra
5th row	Yarra

Value	Count	Frequency (%)
Moreland	1163	8.6%
Boroondara	1160	8.5%
Moonee Valley	997	7.3%
Darebin	934	6.9%
Glen Eira	848	6.2%
Stonnington	719	5.3%
Maribyrnong	692	5.1%
Yarra	647	4.8%
Port Phillip	628	4.6%
Banyule	594	4.4%
Other values (23)	3829	28.2%
(Missing)	1369	10.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
moreland	1163	7.7%
boroondara	1160	7.6%
valley	997	6.6%
moonee	997	6.6%
darebin	934	6.1%
eira	848	5.6%
glen	848	5.6%
stonnington	719	4.7%
maribyrnong	692	4.6%
yarra	665	4.4%
Other values (28)	6172	40.6%

Most occurring characters

Value	Count	Frequency (%)
n	13579	12.3%
o	11999	10.8%
a	11840	10.7%
r	10051	9.1%
e	9358	8.5%
l	6633	6.0%
i	6440	5.8%
M	4120	3.7%
y	3330	3.0%
B	3101	2.8%
Other values (29)	30294	27.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	92566	83.6%
Uppercase Letter	15195	13.7%
Space Separator	2984	2.7%

Most frequent character per category

Value	Count	Frequency (%)
n	13579	14.7%
o	11999	13.0%
a	11840	12.8%
r	10051	10.9%
e	9358	10.1%
l	6633	7.2%
i	6440	7.0%
y	3330	3.6%
t	3082	3.3%
d	3045	3.3%
Other values (11)	13209	14.3%

Value	Count	Frequency (%)
M	4120	27.1%
B	3101	20.4%
P	1256	8.3%
V	997	6.6%
D	986	6.5%
G	900	5.9%
E	848	5.6%
S	719	4.7%
Y	665	4.4%
H	598	3.9%
Other values (7)	1005	6.6%

Value	Count	Frequency (%)
	2984	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	107761	97.3%
Common	2984	2.7%

Most frequent character per script

Value	Count	Frequency (%)
n	13579	12.6%
o	11999	11.1%
a	11840	11.0%
r	10051	9.3%
e	9358	8.7%
l	6633	6.2%
i	6440	6.0%
M	4120	3.8%
y	3330	3.1%
B	3101	2.9%
Other values (28)	27310	25.3%

Value	Count	Frequency (%)
	2984	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	110745	100.0%

Most frequent character per block

Value	Count	Frequency (%)
n	13579	12.3%
o	11999	10.8%
a	11840	10.7%
r	10051	9.1%
e	9358	8.5%
l	6633	6.0%
i	6440	5.8%
M	4120	3.7%
y	3330	3.0%
B	3101	2.8%
Other values (29)	30294	27.4%

Lattitude
Real number (ℝ)

Distinct	6503
Distinct (%)	47.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	-37.80920273
Minimum	-38.18255
Maximum	-37.40853
Zeros	0
Zeros (%)	0.0%
Memory size	106.2 KiB

Quantile statistics

Minimum	-38.18255
5-th percentile	-37.9348
Q1	-37.8568225
median	-37.802355
Q3	-37.7564
95-th percentile	-37.6989385
Maximum	-37.40853
Range	0.77402
Interquartile range (IQR)	0.1004225

Descriptive statistics

Standard deviation	0.0792598226
Coefficient of variation (CV)	-0.002096310339
Kurtosis	1.573252695
Mean	-37.80920273
Median Absolute Deviation (MAD)	0.050455
Skewness	-0.4266949343
Sum	-513448.9731
Variance	0.006282119479
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-37.8361	21	0.2%
-37.7969	16	0.1%
-37.8424	16	0.1%
-37.7609	14	0.1%
-37.8198	13	0.1%
-37.8573	13	0.1%
-37.7634	13	0.1%
-37.8414	13	0.1%
-37.7679	13	0.1%
-37.8161	13	0.1%
Other values (6493)	13435	98.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-38.18255	1	< 0.1%
-38.17488	1	< 0.1%
-38.16802	1	< 0.1%
-38.16762	1	< 0.1%
-38.16624	1	< 0.1%

Value	Count	Frequency (%)
-37.40853	1	< 0.1%
-37.45392	1	< 0.1%
-37.45709	1	< 0.1%
-37.48381	1	< 0.1%
-37.48701	1	< 0.1%

Longtitude
Real number (ℝ_≥0)

Distinct	7063
Distinct (%)	52.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	144.9952162
Minimum	144.43181
Maximum	145.52635
Zeros	0
Zeros (%)	0.0%
Memory size	106.2 KiB

Quantile statistics

Minimum	144.43181
5-th percentile	144.835785
Q1	144.9296
median	145.0001
Q3	145.058305
95-th percentile	145.153631
Maximum	145.52635
Range	1.09454
Interquartile range (IQR)	0.128705

Descriptive statistics

Standard deviation	0.1039155614
Coefficient of variation (CV)	0.0007166826888
Kurtosis	1.758615585
Mean	144.9952162
Median Absolute Deviation (MAD)	0.063415
Skewness	-0.2109908954
Sum	1969035.036
Variance	0.0107984439
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
144.9966	17	0.1%
145.0104	15	0.1%
144.985	14	0.1%
145.0001	13	0.1%
144.991	13	0.1%
144.997	12	0.1%
145.0243	12	0.1%
145.0116	12	0.1%
145.021	12	0.1%
144.9873	12	0.1%
Other values (7053)	13448	99.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
144.43181	1	< 0.1%
144.48571	1	< 0.1%
144.54237	1	< 0.1%
144.54532	1	< 0.1%
144.55106	1	< 0.1%

Value	Count	Frequency (%)
145.52635	1	< 0.1%
145.48273	1	< 0.1%
145.47052	1	< 0.1%
145.45376	1	< 0.1%
145.4453	1	< 0.1%

Regionname
Categorical

Distinct	8
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	106.2 KiB

Southern Metropolitan	4695
Northern Metropolitan	3890
Western Metropolitan	2948
Eastern Metropolitan	1471
South-Eastern Metropolitan	450
Other values (3)	126

Length

Max length	26
Median length	21
Mean length	20.79690722
Min length	16

Characters and Unicode

Total characters	282422
Distinct characters	21
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Northern Metropolitan
2nd row	Northern Metropolitan
3rd row	Northern Metropolitan
4th row	Northern Metropolitan
5th row	Northern Metropolitan

Value	Count	Frequency (%)
Southern Metropolitan	4695	34.6%
Northern Metropolitan	3890	28.6%
Western Metropolitan	2948	21.7%
Eastern Metropolitan	1471	10.8%
South-Eastern Metropolitan	450	3.3%
Eastern Victoria	53	0.4%
Northern Victoria	41	0.3%
Western Victoria	32	0.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
metropolitan	13454	49.5%
southern	4695	17.3%
northern	3931	14.5%
western	2980	11.0%
eastern	1524	5.6%
south-eastern	450	1.7%
victoria	126	0.5%

Most occurring characters

Value	Count	Frequency (%)
t	41064	14.5%
o	36110	12.8%
r	31091	11.0%
e	30014	10.6%
n	27034	9.6%
a	15554	5.5%
i	13706	4.9%
	13580	4.8%
M	13454	4.8%
p	13454	4.8%
Other values (11)	47361	16.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	240782	85.3%
Uppercase Letter	27610	9.8%
Space Separator	13580	4.8%
Dash Punctuation	450	0.2%

Most frequent character per category

Value	Count	Frequency (%)
t	41064	17.1%
o	36110	15.0%
r	31091	12.9%
e	30014	12.5%
n	27034	11.2%
a	15554	6.5%
i	13706	5.7%
p	13454	5.6%
l	13454	5.6%
h	9076	3.8%
Other values (3)	10225	4.2%

Value	Count	Frequency (%)
M	13454	48.7%
S	5145	18.6%
N	3931	14.2%
W	2980	10.8%
E	1974	7.1%
V	126	0.5%

Value	Count	Frequency (%)
	13580	100.0%

Value	Count	Frequency (%)
-	450	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	268392	95.0%
Common	14030	5.0%

Most frequent character per script

Value	Count	Frequency (%)
t	41064	15.3%
o	36110	13.5%
r	31091	11.6%
e	30014	11.2%
n	27034	10.1%
a	15554	5.8%
i	13706	5.1%
M	13454	5.0%
p	13454	5.0%
l	13454	5.0%
Other values (9)	33457	12.5%

Value	Count	Frequency (%)
	13580	96.8%
-	450	3.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	282422	100.0%

Most frequent character per block

Value	Count	Frequency (%)
t	41064	14.5%
o	36110	12.8%
r	31091	11.0%
e	30014	10.6%
n	27034	9.6%
a	15554	5.5%
i	13706	4.9%
	13580	4.8%
M	13454	4.8%
p	13454	4.8%
Other values (11)	47361	16.8%

Propertycount
Real number (ℝ_≥0)

Distinct	311
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	7454.417378
Minimum	249
Maximum	21650
Zeros	0
Zeros (%)	0.0%
Memory size	106.2 KiB

Quantile statistics

Minimum	249
5-th percentile	2185
Q1	4380
median	6555
Q3	10331
95-th percentile	14949
Maximum	21650
Range	21401
Interquartile range (IQR)	5951

Descriptive statistics

Standard deviation	4378.581772
Coefficient of variation (CV)	0.5873808172
Kurtosis	1.217820011
Mean	7454.417378
Median Absolute Deviation (MAD)	2695.5
Skewness	1.069339349
Sum	101230988
Variance	19171978.33
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
21650	359	2.6%
8870	298	2.2%
14949	260	1.9%
10969	249	1.8%
14577	239	1.8%
11918	222	1.6%
9264	220	1.6%
14887	202	1.5%
10412	195	1.4%
11308	191	1.4%
Other values (301)	11145	82.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
249	1	< 0.1%
389	6	< 0.1%
394	2	< 0.1%
438	7	0.1%
457	2	< 0.1%

Value	Count	Frequency (%)
21650	359	2.6%
17496	46	0.3%
17384	3	< 0.1%
17093	13	0.1%
17055	24	0.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Suburb	Address	Rooms	Type	Price	Method	SellerG	Date	Distance	Postcode	Bedroom2	Bathroom	Car	Landsize	BuildingArea	YearBuilt	CouncilArea	Lattitude	Longtitude	Regionname	Propertycount
0	Abbotsford	85 Turner St	2	h	1480000.0	S	Biggin	3/12/2016	2.5	3067.0	2.0	1.0	1.0	202.0	NaN	NaN	Yarra	-37.7996	144.9984	Northern Metropolitan	4019.0
1	Abbotsford	25 Bloomburg St	2	h	1035000.0	S	Biggin	4/02/2016	2.5	3067.0	2.0	1.0	0.0	156.0	79.0	1900.0	Yarra	-37.8079	144.9934	Northern Metropolitan	4019.0
2	Abbotsford	5 Charles St	3	h	1465000.0	SP	Biggin	4/03/2017	2.5	3067.0	3.0	2.0	0.0	134.0	150.0	1900.0	Yarra	-37.8093	144.9944	Northern Metropolitan	4019.0
3	Abbotsford	40 Federation La	3	h	850000.0	PI	Biggin	4/03/2017	2.5	3067.0	3.0	2.0	1.0	94.0	NaN	NaN	Yarra	-37.7969	144.9969	Northern Metropolitan	4019.0
4	Abbotsford	55a Park St	4	h	1600000.0	VB	Nelson	4/06/2016	2.5	3067.0	3.0	1.0	2.0	120.0	142.0	2014.0	Yarra	-37.8072	144.9941	Northern Metropolitan	4019.0
5	Abbotsford	129 Charles St	2	h	941000.0	S	Jellis	7/05/2016	2.5	3067.0	2.0	1.0	0.0	181.0	NaN	NaN	Yarra	-37.8041	144.9953	Northern Metropolitan	4019.0
6	Abbotsford	124 Yarra St	3	h	1876000.0	S	Nelson	7/05/2016	2.5	3067.0	4.0	2.0	0.0	245.0	210.0	1910.0	Yarra	-37.8024	144.9993	Northern Metropolitan	4019.0
7	Abbotsford	98 Charles St	2	h	1636000.0	S	Nelson	8/10/2016	2.5	3067.0	2.0	1.0	2.0	256.0	107.0	1890.0	Yarra	-37.8060	144.9954	Northern Metropolitan	4019.0
8	Abbotsford	6/241 Nicholson St	1	u	300000.0	S	Biggin	8/10/2016	2.5	3067.0	1.0	1.0	1.0	0.0	NaN	NaN	Yarra	-37.8008	144.9973	Northern Metropolitan	4019.0
9	Abbotsford	10 Valiant St	2	h	1097000.0	S	Biggin	8/10/2016	2.5	3067.0	3.0	1.0	2.0	220.0	75.0	1900.0	Yarra	-37.8010	144.9989	Northern Metropolitan	4019.0

Last rows

	Suburb	Address	Rooms	Type	Price	Method	SellerG	Date	Distance	Postcode	Bedroom2	Bathroom	Car	Landsize	BuildingArea	YearBuilt	CouncilArea	Lattitude	Longtitude	Regionname	Propertycount
13570	Wantirna South	34 Fewster Dr	3	h	970000.0	S	Barry	26/08/2017	14.7	3152.0	3.0	2.0	2.0	674.0	NaN	NaN	NaN	-37.88360	145.22805	Eastern Metropolitan	7082.0
13571	Wantirna South	15 Mara Cl	4	h	1330000.0	S	Barry	26/08/2017	14.7	3152.0	4.0	2.0	2.0	717.0	191.0	1980.0	NaN	-37.86887	145.22116	Eastern Metropolitan	7082.0
13572	Watsonia	76 Kenmare St	2	h	650000.0	PI	Morrison	26/08/2017	14.5	3087.0	2.0	1.0	1.0	210.0	79.0	2006.0	NaN	-37.70657	145.07878	Northern Metropolitan	2329.0
13573	Werribee	5 Nuragi Ct	4	h	635000.0	S	hockingstuart	26/08/2017	14.7	3030.0	4.0	2.0	1.0	662.0	172.0	1980.0	NaN	-37.89327	144.64789	Western Metropolitan	16166.0
13574	Westmeadows	9 Black St	3	h	582000.0	S	Red	26/08/2017	16.5	3049.0	3.0	2.0	2.0	256.0	NaN	NaN	NaN	-37.67917	144.89390	Northern Metropolitan	2474.0
13575	Wheelers Hill	12 Strada Cr	4	h	1245000.0	S	Barry	26/08/2017	16.7	3150.0	4.0	2.0	2.0	652.0	NaN	1981.0	NaN	-37.90562	145.16761	South-Eastern Metropolitan	7392.0
13576	Williamstown	77 Merrett Dr	3	h	1031000.0	SP	Williams	26/08/2017	6.8	3016.0	3.0	2.0	2.0	333.0	133.0	1995.0	NaN	-37.85927	144.87904	Western Metropolitan	6380.0
13577	Williamstown	83 Power St	3	h	1170000.0	S	Raine	26/08/2017	6.8	3016.0	3.0	2.0	4.0	436.0	NaN	1997.0	NaN	-37.85274	144.88738	Western Metropolitan	6380.0
13578	Williamstown	96 Verdon St	4	h	2500000.0	PI	Sweeney	26/08/2017	6.8	3016.0	4.0	1.0	5.0	866.0	157.0	1920.0	NaN	-37.85908	144.89299	Western Metropolitan	6380.0
13579	Yarraville	6 Agnes St	4	h	1285000.0	SP	Village	26/08/2017	6.3	3013.0	4.0	1.0	1.0	362.0	112.0	1920.0	NaN	-37.81188	144.88449	Western Metropolitan	6543.0

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows